ReviewZhongguo fei ai za zhi = Chinese journal of lung cancer2018
[Research Progress of Raman Spectroscopy in the Diagnosis of Early Lung Cancer].
Review in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
- Deep Learning Model as a New Trend in Computer-aided Diagnosis of Tumor Pathology for Lung Cancer.Journal of Cancer · 2020Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer (LC) is the most common cancer and the leading cause of cancer-related death worldwide. The 5-year survival rate for LC remains low at 18% and is 5% for patients with metastatic disease, while the 5-year overall survival rate of patients with stage I NSCLC can reach 77.9%, hence early diagnosis and treatment of LC is the key to improve the prognosis. As a non-invasive detection technique, Raman spectroscopy can realize the non-destructive detection of the differences in molecular level structure between cancerous tissues and normal tissues, which can be used for the early diagnosis of lung cancer. The aim of this review is to summarize the progress of Raman spectroscopycombined with different tissue or body fluid samplesin the diagnosis of early LC. .
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Registered trials
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